Sr GenAI Infra Specialist SA, AWS WWSO Startup

About the role

This role sits at the intersection of AI infrastructure architecture and model optimization — you will help customers understand hardware requirements and complexity (GPU, Trainium, networking), while also providing deep expertise in optimization of models and techniques for both inference serving and distributed training at scale.

Responsibilities

• Work directly with the most important and exciting Startup customers in the GenAI model training and inference space, helping them adopt and scale large-scale workloads (e.g., frontier models, models, multi-modal systems, optimization) on AWS
• Advise customers on AI infrastructure requirements and trade-offs including GPU/Trainium selection, cluster topology, storage, networking (EFA), and cost optimization for training and inference
• Provide deep technical guidance on inference optimization model serving architectures (self-managed on EKS, SageMaker endpoints, Sagemaker Hyperpod Serving), batching strategies, quantization, model parallelism, and latency/throughput tradeoffs
• Provide deep technical guidance on training optimization distributed training strategies, framework selection (PyTorch, JAX, NeMo), SageMaker HyperPod, Slurm/PCS integration, checkpointing, and data pipeline design
• Guide customers on GPU and accelerator profiling identifying bottlenecks (compute, memory, I/O), optimizing utilization, and tuning system-level performance
• Help customers understand and apply model optimization techniques fine-tuning approaches (LoRA, QLoRA, full fine-tuning), RLHF/DPO, knowledge distillation, and efficient serving techniques (vLLM, TensorRT-LLM, Triton)
• Help Go-To-Market Specialist define and drive strategy on assets that impact growth through market sizing, building an opportunity pipeline, creating technical content to train field teams, and establishing thought leadership
• Develop demos, proof-of-concepts, reference architectures, and benchmarks that demonstrate AWS infrastructure value proposition for GenAI workloads
• Collaborate with product teams (EC2, Trainium/Inferentia, SageMaker, EKS, PCS, EC2) to shape product vision, prioritize features, and represent the voice of the customer
• Work with account teams, research scientists, ISVs, framework communities, and model providers to drive implementations and accelerate innovation

Qualifications

• Experience conveying complex technical concepts to both technical and business audiences
• 8+ years of experience in technology domain areas (e.g., systems engineering, cloud infrastructure, HPC, ML/AI, distributed computing)
• 3+ years of experience designing, implementing, or consulting on large-scale AI/ML infrastructure with hands-on experience on GPU-based computing, ML training infrastructure, and inference serving systems